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Probability and Statistics for Engineering and the Sciences with Modeling using R
Beschreibung:
The primary goal behind this book is offering the flexibility for instructors to build most undergraduate courses upon it. This book is designed for either a one-semester course in either introductory probability and statistics (not calculus-based) and/or a one-semester course in a calculus-based probability and statistics course.
1. Introduction to Statistical Modeling and Models and R. 2. Introduction to Data. 3. Statistical Measures. 4. Classical Probability. 5. Discrete Distributions. 6. Continuous Probability Models. 7. Other Continuous Distribution (some calculus required): Triangular, Unnamed, Beta, Gamma. 8. Sampling Distributions. 9. Estimating Parameters. 10. One Sample Hypothesis Testing. 11. Two Sample Hypothesis Testing. 12. Reliability Modeling. 13. Introduction to Regression Techniques. 14. Advanced Regression Models: Nonlinear, Sinusoidal, and Binary Logistics Regression using R. 15. ANOVA in R. 16. Two-way ANCOVA using R.
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